MSI

MSI EdgeXpert

MSI's high-efficiency GB10 architecture framework designed for unthrottled sustained execution of autonomous AI agents.

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Quick Specs

VRAM128 GB

FP1629.71 TFLOPS

Our Take

Best for: Datacenter inference for flagship dense models

Sized for production serving of 70B–200B class models at full or lightly-quantized precision. Overkill for a homelab; right call when the workload pays for itself in token volume.

Pair this withKimi K2.7 Code (1000B)Largest popular open model that fits at Q4 — needs roughly 86.2 GB on this 128 GB card.

Generated from this product’s spec sheet. Editor reviews refine it over time.

Specifications

The MSI EdgeXpert represents a significant shift in edge computing, moving away from traditional consumer GPUs toward a specialized framework designed for sustained, unthrottled AI execution. Built on the NVIDIA GB10 (Grace Blackwell) architecture, this is not a standard workstation; it is a compact AI supercomputer engineered to bridge the gap between desktop development and data center deployment.

While the EdgeXpert shares its DNA with the NVIDIA DGX Spark platform, MSI’s implementation focuses on thermal headroom and power delivery to outpace the reference design. For AI engineers and agents-focused developers, the EdgeXpert is a "black box" solution that provides a massive 128GB unified memory pool, making it one of the most capable pieces of hardware for running large-scale models locally.

AI Performance & Specifications

The core of the MSI EdgeXpert is the GB10 Superchip, which integrates a 20-core Arm CPU with a Blackwell-architecture GPU via the NVLink-C2C interconnect. This high-speed bridge eliminates the PCIe bottleneck commonly found in multi-GPU setups, providing a unified memory architecture that is essential for agentic workflows where context must be swapped rapidly.

VRAM & Unified Memory: 128 GB LPDDR5x. This is the standout spec. Unlike consumer cards capped at 24GB, this allows for massive model weights and long context windows to reside entirely in memory.

Models That Run on This Device

The top models this device can run at 4-bit, ranked by fit and speed.

Model	Grade	Speed	VRAM
Qwen3-30B-A3BAlibaba	SS	40.8 tok/s	5.4 GB
LFM2.5-8B-A1BLiquid AI	AA	75.6 tok/s	2.9 GB
Llama 3 8B InstructMeta	AA	38.8 tok/s	5.7 GB
Carnice-9b for Hermes agentkai-os	AA	36.5 tok/s	6.0 GB
PersonaPlex 7BNVIDIA

Plan Your Setup

Compute Throughput: 29.71 TFLOPS (FP16) and 250 TOPS (INT8). For those utilizing lower precision, it reaches up to 1000 AI TOPS at FP4.

Memory Bandwidth: 273 GB/s. While lower than H100/A100 class hardware, the coherent memory access between the Arm cores and the GPU ensures high efficiency for data preprocessing and orchestration.

Thermal Engineering: MSI has re-engineered the cooling system to allow the unit to draw 12% more power (140W TDP) than the reference design. This results in roughly 10% higher sustained performance, as the unit avoids the thermal throttling that often plagues small-form-factor AI PCs.

What Models Can It Run?

The MSI EdgeXpert is specifically designed for the "200B parameter" threshold. For practitioners, this means moving beyond 70B models and into the territory of frontier-class local inference.

Large Language Models (LLMs)

Llama 3.1 405B: While the full FP16 model exceeds the 128GB VRAM, the EdgeXpert can run Llama 3.1 405B at heavy quantization (IQ2_M or similar). However, the "sweet spot" is Llama 3.1 70B, which can run at FP16 or high-bitrate GGUF/EXL2 with massive context windows (128k+ tokens) without spilling into system RAM.
DeepSeek-V3 / DeepSeek-R1: The 128GB VRAM capacity allows for comfortable execution of 671B MoE (Mixture of Experts) models at 1.5-bit to 2-bit quantization, or the smaller 32B/70B distillations at maximum precision with high throughput.
Grok-1: With 128GB, you can run Grok-1 (314B parameters) at 2-bit or 3-bit quantization, enabling local research on one of the largest open-weight models available.

Multimodal & Agentic Workflows

The 20-core Arm architecture (Cortex-X925/A725) is purpose-built for the "orchestration" layer of AI agents. In a typical agentic loop, the CPU handles tool use, API calls, and code execution while the GPU handles inference. The NVLink-C2C ensures that the handoff between the LLM "brain" and the CPU "actuator" happens with minimal latency.

Use Cases & Target Audience

The MSI EdgeXpert is positioned as the premier "best AI PC for running models locally" for users who find 24GB consumer cards too restrictive and $30,000 enterprise H100s too expensive.

Autonomous Agent Developers: The sustained 140W TDP and high VRAM make it ideal for agents that need to run 24/7, processing RAG (Retrieval-Augmented Generation) pipelines and multi-step reasoning tasks.
Privacy-First Enterprises: Organizations that cannot leak proprietary data to cloud APIs can run 70B+ parameter models locally for document analysis, code generation, and internal knowledge bases.
Edge AI Deployment: With its compact 151 x 151 x 52 mm footprint and 10 GbE ConnectX-7 networking, the EdgeXpert is a "drop-in" server for on-site inference in medical, industrial, or secure facility environments.

MSI EdgeXpert vs. Mac Studio (M2/M3 Ultra)

The Mac Studio is the most common competitor for high-VRAM local inference. While the Mac can offer up to 192GB of unified memory, the EdgeXpert has a distinct advantage in the software ecosystem. As an NVIDIA-certified system, the EdgeXpert provides native support for the full CUDA stack, TensorRT, and NVIDIA AI Enterprise. If your workflow relies on Triton kernels, FlashAttention-2, or specific CUDA-accelerated libraries, the EdgeXpert is the more compatible choice.

MSI EdgeXpert vs. Multi-RTX 4090 Builds

A dual RTX 4090 setup provides 48GB of VRAM and higher raw TFLOPS, but at the cost of 900W+ power draw, massive heat, and the complexity of multi-GPU peer-to-peer communication. The EdgeXpert offers nearly 3x the VRAM of a single 4090 in a chassis the size of a lunchbox, drawing only 140W. For running large models (100B+ parameters) where VRAM capacity is the primary bottleneck rather than raw compute speed, the EdgeXpert is the more efficient and capable tool.

For engineers building the next generation of local AI agents, the MSI EdgeXpert provides the specific combination of high-capacity unified memory and NVIDIA-native software compatibility required for unconstrained development.